Amigo AI · New York
OtherFieldFullTimeposted 2mo ago
At Amigo, we're building the clinical AI infrastructure that health systems, life sciences companies, payors, and government agencies run their patient-facing care on. Our agents work across the whole patient journey: pre-visit intake, care navigation, post-visit care plans, and ongoing monitoring. Our mission is to make excellent care accessible to every patient, not rationed by the limits of clinician time.
This hasn’t been solved because the underlying record was never built for it. EHRs were designed for billing, not for systems that learn. So instead of layering another point solution on top, we’re rebuilding the medical record as a timeline of clinical events and running agents on top of it that improve with every patient interaction. Unlike single-purpose chatbots or scribes, Amigo is the platform our customers use to build their own agents. That means our work has to hold up across specialties, workflows, and regulatory environments and not just one narrow use case.
Our agents have supported more than 4 million patient encounters and are on track to grow tenfold this year. Our work is validated through partnerships with leading academic medical institutions. We’re fresh off our Series A, backed by Tier 1 VCs such as Madrona, General Catalyst, and Optum Ventures.
We’re a small team of around 35 people, working in person in New York City and San Francisco. We care deeply about craft, clinical rigor, and the speed at which good ideas reach patients. If you want your work to be measured in outcomes rather than releases, we’d like to hear from you.
As an Staff Forward Deployed Engineer at Amigo, you'll lead the technical delivery of customer deployments end to end. You'll set the architecture, break big ambiguous problems into work a team can own, commit the timelines, and hold the bar for what ships. It's a hands-on leadership role at the intersection of engineering, product, and the customer.
Depending on your strengths, the role leans toward deep technical leadership, people leadership, or both. Some tech leads are the deepest technical authority on the team and take the hardest problems themselves. Others manage a handful of engineers and own how the team operates. Most do some of each. We work out the shape with you.
Leading an AI deployment for a major healthcare customer, from first conversation to production
Turning an ambiguous customer need into a clear technical plan with owners and timelines
Setting the architecture and engineering standards the team builds within
Making the calls on tradeoffs: what to build now, what to reuse, and what to push back on
Growing the engineers around you and raising the bar of the whole team
Working directly with customers to keep scope, timelines, and quality honest
You've led significant engineering work end to end, as a tech lead, staff engineer, or engineering manager
You've broken hard, ambiguous problems into work other engineers could own and deliver
You have real experience with LLMs and agent systems, or the depth to get there fast
You have the judgment to make tradeoffs and the standing to say no when something doesn't hold up
You lead well, whether through architecture, through people, or both
You're low ego, direct, and hold yourself and your team to a high bar
You can work on site in New York City or San Francisco
Experience in a regulated or high-reliability domain (healthcare, finance, legal)
Experience shipping production AI or ML systems
Background in customer-facing or forward-deployed engineering
Experience growing engineers or running a small team
Comprehensive health, dental, and vision insurance
Daily catered lunch and dinner
Mental health support and wellness coaching
Flexible wellness stipend for fitness, therapy, or personal growth
Annual learning budget for courses, books, or conferences
Conference attendance budget for professional development
Annual team offsite
Academic collaboration opportunities
Unlimited PTO
Patients Win, We Win
If patients aren't getting better care, we haven't earned the right to scale. Every internal decision gets pressure-tested: does this make patients' lives better? If we can't draw the line, we question why we're doing it.
High Standards, High Care
We hold a high bar for the team because patients are counting on us to get this right. But high standards only work with genuine investment in each other. You can take risks, admit mistakes, and challenge ideas—not despite our standards, but because of them.
Thoughtful Urgency
We move fast by default, but speed without judgment is recklessness. The discipline is knowing which decisions are reversible vs. not. In healthcare AI, the companies that win will be fast everywhere they can be and careful everywhere they must be. We build the muscle to do both.
Intensely Measured
We instrument patient outcomes, provider ROI, system performance, and clinical accuracy. But data without action is surveillance. Every metric should have an owner, a threshold, and a response plan. If we're measuring something but never acting on it, we stop measuring it.
Low ego: Politics and territory don't interest you. The best ideas win, regardless of who has them.
Direct: You say the hard thing, challenge ideas openly, and commit fully once decided.
High agency: You thrive on trust rather than instruction. When you see something is broken, you fix it. You don’t file tickets and wait for someone else.
Bar of excellence: You hold yourself to a bar most people wouldn't, and you want teammates who do the same.
Skeptical: You push back on rules that don’t make sense and question assumptions that haven’t earned their place.